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Writer's pictureEdgar Kraychik

Data-Driven Enterprise can't be implemented without this role.

According to Marx's theory of Dialectic Materialism, a Quantity has a Quality of its Own. In other words, sufficient amounts of "stuff" will inevitably lead to changes in the nature and the use of the "stuff". This holds true in the 21st Century in general, and for the Data Platforms in particular. Data Lakes, assuming they are properly build and virtualized, provide the most accurate single view of the historical data, in all their multi-faceted and multi-velocity richness.


Typically, the responsibility is with the IT department to capture data from all natural business transactions: sales, inventory, finance, online clickstream, mobile. Some forward-thinking IT shops are going far beyond, and are capturing mobile app usage, online behavioral patterns (clickthrough, cart abandons, etc.) and IOT data. Yet, the most advance IT teams are now looking for near real-time store traffic data. And we are collecting petabytes of this data! However, as much as you think it is, it is not enough! All of these are parochially-based datasets and, thus are not sufficient. To address, we bring-in External sources (social, competitor action, partner delivery, 3rd party IOT, etc) and Augmentor sources (householding, data cleansing, Do Not Promote, etc.)


I am convinced that we need to capture as much data as possible, even without an immediate ability use it, even if we don’t understand the use-case immediately! Moreover, we need to religiously monitor and continuously improve data quality. There are 9 key dimension that I recommend to monitor through a Kiviat (spider web/radar) chart on a regular basis:


In addition, we need to implement a sound Data Governance framework to prevent decay of the data quality and to ensure its continuous Improvement .


Now, the obvious questions are: What is the incentive for CIO to improve the Data Quality? How aligned is the goal of improving Data Quality with key CIO objectives of lowering cost-base, and providing the most efficient method of aggregating and exposing data? Is improving the state of data something a typical CIO truly cares about, hast expertise in, or has time to focus on?


My hunch is - No! IT is not in a business of delivering high Data Quality as a practice. Besides being Accurate and Timely, there is no incentive for IT to make promote Representation, Interpretation, Use and Measurement aspects of a Data-driven enterprise. As a result, many companies end up with silos of poorly integrated, duplicate data of dubious accuracy. The real risk here is that no amount of system or analytical intelligence is going to improve if data is garbage. Engineering Knowledge or AI is not going to help! Garbage-in-garbage out!


There are more and more reports being published, confirming my belief that most companies are lacking a comprehensive, centralized Data Management strategy. There is a tremendously convincing case for creating a CDO (Chief Data Officer) role independent of IT, Marketing, Operations or any other business units. The game-changing opportunities in the art of Data Management that are best be pursued with an obsessive focus.


CDO is a mix role of business and technology background (mostly technology), whole sole role is to instrument a data advantage for the company. To ensure that, from operational systems to analytical ones, from ingestion to provisioning, from back-end to front-end systems, we are capturing and analyzing data to create faster and better convergence of the key strategic objectives. These could be higher NPS, faster time to market, better customer intimacy, competitor insights, reduced churn, more intimate customer personalization, faster fulfillment, etc.


As AI, inevitably, is going to take a hold in day-to-day business operations, the only competitive advantage incumbents will have is Data. Data is NOT a DURABLE asset and we need to baby it, every GB of it! Put someone in charge of it. This person, a CDO, should have an obsessive focus, and should be measured on converting petabytes of facts into an actionable intelligence that will drive your business growth beyond immediate horizons.

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